Social‐Behavioral Simulation: Key Challenges

Carley, Kathleen M.

doi:10.1002/9781119485001.ch32

Cited by 13 publications

(3 citation statements)

References 17 publications

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“…Resonating with recent scholarship on identity propaganda as a framework for online harms (Reddi et al, 2021), we sought to characterize hate speech in online discourse about racism through the use of identity terms, the use of which we counted with the NetMapper software (Altman et al, 2017; K. M. Carley, 2014; L. R. Carley et al, 2018).…”

Section: Methodsmentioning

confidence: 99%

Bots Amplify and Redirect Hate Speech in Online Discourse About Racism During the COVID-19 Pandemic

Uyheng

Bellutta

Carley

2022

Social Media + Society

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Online talk about racism has been salient throughout the COVID-19 pandemic. Yet while such social media conversations reflect existing tensions in the offline world, the same discourse has also become a target for information operations aiming to heighten social divisions. This article examines Twitter discussions of racism in the first and sixth months since COVID-19 was accorded pandemic status by the World Health Organization and uncovers dynamic associations with bot activity and hate speech. Humans initially constituted the most hateful accounts in online conversations about racism in March, but in August, bots dominated hate speech. Over time, greater bot activity likewise amplified levels of hate speech a week later. Moreover, while discourse about racism in March primarily featured an organic focus on racial identities like Asian and Chinese, we further observed a bot-dominated focus in August toward political identities like president, Democrat, and Republican. Although hate speech targeting Asian groups remained present among racism discussions in August, these findings suggest a bot-fueled redirection from focusing on racial groups at the onset of the pandemic to targeting politics closer to the 2020 US elections. This work enhances understanding of the complexity of racism discussions during the pandemic, its vulnerability to manipulation through information operations, and the large-scale quantitative study of inorganic hate campaigns in online social networks.

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Section: Methodsmentioning

confidence: 99%

Bots Amplify and Redirect Hate Speech in Online Discourse About Racism During the COVID-19 Pandemic

Uyheng

Bellutta

Carley

2022

Social Media + Society

Self Cite

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“…It is thus possible that some of the challenges experienced by modelers in the next sections stem from the high cost of re-creating solutions and re-discovering issues, instead of seeking and integrating building blocks developed for a similar purpose. As reuse is a known challenge for social-behavioral simulations, we refer the reader to (Carley 2019) for a separate discussion.…”

Section: Background: Developing Simulation Models For Covid-19mentioning

confidence: 99%

Opportunities and Challenges in Developing COVID-19 Simulation Models: Lessons from Six Funded Projects

Giabbanelli

Badham

Castellani

et al. 2021

2021 Annual Modeling and Simulation Conference (ANNSIM)

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The COVID-19 pandemic showed us the importance of modeling and forecasting efforts to guide decision makers. However, a year into the COVID-19 pandemic, the computational science literature lacks a proper internal exploration of the modeling journey of researchers around the world, including how they responded to the shared challenges our community faced such as data limitations, model fitting and working with public stakeholders. The current paper is a detailed examination of the internal processes of six research teams, which were funded in several countries to model COVID-19. Each team was asked to reflect on the research question and how they solved their respective modeling challenges, as well as how, looking back, they would do things differently.

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“…The social capital approach focuses on quantitative methodologies for network analysis (e.g., Lin et al, 2001). The structuralism approach favors parsimonious arguments and employs quantitative methods including computational simulations to test hypotheses (e.g., Carley 2019). The network form of organization approach takes an organizational-level focus on institutions that often includes historical and qualitative methods (e.g., Smith-Doerr and Powell 2005).…”

mentioning

confidence: 99%

Social capital, structuralism, and organizational form: Three social network theory perspectives for research in higher education

Smith‐Doerr

Yates

Knaub

2022

Equity in Education & Society

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Social network analysis offers much for understanding educational contexts, including inequalities. However, adoption of network methods has not always been accompanied by clear understanding of network theoretical assumptions. With an eye to closing the gap between network methods and theory, literature from three major theoretical perspectives on social networks is reviewed. First, social capital comes from network ties providing access to beneficial outcomes, often material resources. Second, structuralism assumes primacy of network structures, and largely disregards individual agency. Third, at the organizational level, the network form of organization contrasts to hierarchies. Each perspective has conceptual strengths and weaknesses. Critical views are also needed; network research should disrupt inequalities in education.

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Social‐Behavioral Simulation: Key Challenges

Cited by 13 publications

References 17 publications

Bots Amplify and Redirect Hate Speech in Online Discourse About Racism During the COVID-19 Pandemic

Bots Amplify and Redirect Hate Speech in Online Discourse About Racism During the COVID-19 Pandemic

Opportunities and Challenges in Developing COVID-19 Simulation Models: Lessons from Six Funded Projects

Social capital, structuralism, and organizational form: Three social network theory perspectives for research in higher education

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